{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lesson 14.2 - Plotting with Seaborn: Choosing color palettes\n",
    "\n",
    "*Facsimile of [Seaborn tutorial](http://stanford.edu/~mwaskom/software/seaborn/tutorial.html).*\n",
    "\n",
    "Color is more important than other aspects of figure style because color can reveal patterns in the data if used effectively or hide those patterns if used poorly. There are a number of great resources to learn about good techniques for using color in visualizations, I am partial to this [series of blog posts](http://earthobservatory.nasa.gov/blogs/elegantfigures/2013/08/05/subtleties-of-color-part-1-of-6/) from Rob Simmon and this [more technical paper](http://www.sandia.gov/~kmorel/documents/ColorMaps/ColorMapsExpanded.pdf). The matplotlib docs also now have a [nice tutorial](http://matplotlib.org/users/colormaps.html) that illustrates some of the perceptual properties of the built in colormaps.\n",
    "\n",
    "Seaborn makes it easy to select and use color palettes that are suited to the kind of data you are working with and the goals you have in visualizing it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set(rc={\"figure.figsize\": (6, 6)})\n",
    "np.random.seed(sum(map(ord, \"palettes\")))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Building color palettes with `color_palette`\n",
    "\n",
    "The most important function for working with discrete color palettes is `color_palette`. This function provides an interface to many (though not all) of the possible ways you can generate colors in seaborn, and it's used internally by any function that has a `palette` argument (and in some cases for a `color` argument when multiple colors are needed).\n",
    "\n",
    "`color_palette` will accept the name of any seaborn palette or matplotlib colormap (except `jet`, [which you should never use](http://medvis.org/2012/08/21/rainbow-colormaps-what-are-they-good-for-absolutely-nothing/)). It can also take a list of colors specified in any valid matplotlib format (RGB tuples, hex color codes, or HTML color names). The return value is always a list of RGB tuples.\n",
    "\n",
    "Finally, calling `color_palette` with no arguments will return the current default color cycle.\n",
    "\n",
    "A corresponding function, `set_palette`, takes the same arguments and will set the default color cycle for all plots. You can also use `color_palette` in a `with` statement to temporarily change the default palette (see below on palette contexts).\n",
    "\n",
    "It is generally not possible to know what kind of color palette or colormap is best for a set of data without knowing about the characteristics of the data. Following that, we'll break up the different ways to use `color_palette` and other seaborn palette functions by the three general kinds of color palettes: *qualitative*, *sequential*, and *diverging*."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Qualitative color palettes\n",
    "\n",
    "Qualitative (or categorical) palettes are best when you want to distinguish discrete chunks of data that do not have an inherent ordering.\n",
    "\n",
    "After importing seaborn, you can run `sns.set()` to change the default color cycle to a set of six colors that evoke the standard matplotlib color cycle while aiming to be a bit more pleasing to look at."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we can get the current palette using `sns.color_palette()` and display the color palette using `sns.palplot()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "current_palette = sns.color_palette()\n",
    "sns.palplot(current_palette)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are six variations of the default theme, called ``deep``, ``muted``, ``pastel``, ``bright``, ``dark``, and ``colorblind``."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for variation in ['deep', 'muted', 'pastel', 'bright', 'dark', 'colorblind']:\n",
    "    current_palette = sns.color_palette(variation)\n",
    "    sns.palplot(current_palette)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice we haven't changed the default colormap yet:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([0, 1], [0, 1])\n",
    "plt.plot([0, 1], [0, 2])\n",
    "plt.plot([0, 1], [0, 3]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have to run `sns.set_palette()` to change the default colormap, to what `current_palette` was after the last for loop:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_palette(current_palette)\n",
    "\n",
    "plt.plot([0, 1], [0, 1])\n",
    "plt.plot([0, 1], [0, 2])\n",
    "plt.plot([0, 1], [0, 3]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Using circular color systems\n",
    "\n",
    "When you have more than six categories to distinguish, the easiest thing is to draw evenly-spaced colors in a circular color space (such that the hue changes which keeping the brightness and saturation constant). This is what most seaborn functions default to when they need to use more colors than are currently set in the default color cycle.\n",
    "\n",
    "The most common way to do this uses the ``hls`` color space, which is a simple transformation of RGB values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"hls\", 12))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is also the `hls_palette` function that lets you control the lightness and saturation of the colors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.hls_palette(8, l=.3, s=.8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, because of the way the human visual system works, colors that are even \"intensity\" in terms of their RGB levels won't necessarily look equally intense. [We perceive](http://en.wikipedia.org/wiki/Color_vision) yellows and greens as relatively brighter and blues as relatively darker, which can be a problem when aiming for uniformity with the ``hls`` system.\n",
    "\n",
    "To remedy this, seaborn provides an interface to the [husl](http://www.boronine.com/husl/) system, which also makes it easy to select evenly spaced hues while keeping the apparent brightness and saturation much more uniform."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAdgAAABQCAYAAAC6TWSYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvqOYd8AAAAlZJREFUeJzt3T1qVFEcxuFzTRSTIZGQxsEd6DosREWntxIsXICFFrbW1oJV+lE0WLgOXYDN2ATJDDPiBxzXkMu8nMv1efo/vKf6wW1uV2utBQDYqkutBwDAGAksAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAE7PY9/PX6pNTz1Ta3DMbVl0/Ll7d3W8+IufX4tJzMx/u+R7PTcu/z89YzIj7eflUefHrXekbM+zsPy+zD19YzYub3b5b5m03rGTGzJ/tl8+xb6xkR3dFO2Xtx40I3vQNbz1el/lj2PR+838tF6wlRq/W437f4edZ6Qsxis249Ier7+k/rCVHr5bh/YFbP/raeMBg+EQNAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkCAwAJAgMACQIDAAkDAbt/D7trBNncMzpXDaesJUQeTcb9vunfcekLMdH/SekLU9cnl1hOiJodd6wlR3XHvrAxad7Rz8Ztaaw1sAYD/mk/EABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAEPAPCWo+kvcOx0cAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"husl\", 8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is similarly a function called `husl_palette` that provides a more flexible interface to this system."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Using categorical Color Brewer palettes\n",
    "\n",
    "Another source of visually pleasing categorical palettes comes from the [Color Brewer](http://colorbrewer2.org/) tool (which also has sequential and diverging palettes, as we'll see below). These also exist as matplotlib colormaps, but they are not handled properly. In seaborn, when you ask for a qualitative Color Brewer palette, you'll always get the discrete colors, but this means that at a certain point they will begin to cycle.\n",
    "\n",
    "A nice feature of the Color Brewer website is that it provides some guidance on which palettes are color blind safe. There are a variety of [kinds](http://en.wikipedia.org/wiki/Color_blindness) of color blindness, but the most common variant leads to difficulty distinguishing reds and greens. It's generally a good idea to avoid using red and green for plot elements that need to be discriminated based on color.\n",
    "\n",
    "Use the free program [Color Oracle](http://www.colororacle.org) to see how people with color blindness see the world."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArgAAABQCAYAAADySAbpAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvqOYd8AAAAwtJREFUeJzt2r9LVWEAxvHX1PCShFwCM4Qa2hoaK6ilgqaaJNA/Itqaiqiprcb+gYSIFidRmoJsbI2GAsmIEAnlhj+6zY5d7ssrD5/PcqYXnsOBc77DGen3+/0CAAAhjrUeAAAAwyRwAQCIInABAIgicAEAiCJwAQCIInABAIgicAEAiCJwAQCIInABAIgicAEAiCJwAQCIInABAIgyNujBlc8/S2/vYJhbjow7F2bK1WfvWs+o5v2D62V1/WXrGVW8WHtbluaWy+03t1pPqWJpbrnsL75qPaOasfmFsnHpSusZ1cx8/FD+rj1pPaOaY5cflfL8XOsZ9dz/Wj6tfmm9ooqLN8+Xh3cXW8+o5unr+VJK7ruzlIWycu9G6xFVTHSny7XH///sBg7c3t5B2dnNDNxSSlnf6rWeUFVv/3frCVVs7Hw/dI20vd16QVUH6+utJ9T1Z7P1grq2vrVeUNVub6/1hGo2f2S/W0rJvr/er+Dv3gD8ogAAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAEAUgQsAQBSBCwBAFIELAECUsUEPdsZHh7njyJmd6rSeUFVn7GTrCVXMnDhz6BppcrL1gqpGZ2dbT6hrott6QV1TZ1svqOp4Z7z1hGq6p7PfLaVk31/nVOZ3b6I7PdC5kX6/3x/yFgAAaMYvCgAARBG4AABEEbgAAEQRuAAARBG4AABEEbgAAEQRuAAARBG4AABEEbgAAEQRuAAARBG4AABEEbgAAET5Bx+pVLpkA8pBAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"Paired\", 12))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"Set2\", 10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To help you choose palettes from the Color Brewer library, there is the `choose_colorbrewer_palette` function. This function, which must be used in an IPython notebook, will launch an interactive widget that lets you browse the various options and tweak their parameters.\n",
    "\n",
    "Of course, you might just want to use a set of colors you particularly like together. Because `color_palette` accepts a list of colors, this is easy to do."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "flatui = [\"#9b59b6\", \"#3498db\", \"#95a5a6\", \"#e74c3c\", \"#34495e\", \"#2ecc71\"]\n",
    "sns.palplot(sns.color_palette(flatui))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Using named colors from the xkcd color survey\n",
    "\n",
    "A while back, [xkcd](http://xkcd.com/) ran a [crowdsourced effort](http://blog.xkcd.com/2010/05/03/color-survey-results/) to name random RGB colors. This produced a set of [954 named colors](http://xkcd.com/color/rgb/), which you can now reference in seaborn using the ``xkcd_rgb`` dictionary:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1a2c2dd518>]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([0, 1], [0, 1], sns.xkcd_rgb[\"rust\"], lw=3)\n",
    "plt.plot([0, 1], [0, 2], sns.xkcd_rgb[\"lilac\"], lw=3)\n",
    "plt.plot([0, 1], [0, 3], sns.xkcd_rgb[\"navy\"], lw=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want to spend some time picking colors, this [interactive visualization](http://www.luminoso.com/colors/) may be useful. In addition to pulling out single colors from the ``xkcd_rgb`` dictionary, you can also pass a list of names to the `xkcd_palette` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = [\"windows blue\", \"amber\", \"greyish\", \"faded green\", \"dusty purple\"]\n",
    "palette = sns.xkcd_palette(colors)\n",
    "sns.set_palette(palette)\n",
    "sns.palplot(palette)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The color palette set by `sns.set_palette()` will then be the default:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([0, 1], [0, 0], lw=3)\n",
    "plt.plot([0, 1], [0, 1], lw=3)\n",
    "plt.plot([0, 1], [0, 2], lw=3)\n",
    "plt.plot([0, 1], [0, 3], lw=3)\n",
    "plt.plot([0, 1], [0, 4], lw=3);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sequential color palettes\n",
    "\n",
    "The second major class of color palettes is called \"sequential\". This kind of color mapping is appropriate when data range from relatively low or unintersting values to relatively high or interesting values. Although there are cases where you will want discrete colors in a sequential palette, it's more common to use them as a colormap in functions like `kdeplot` or `corrplot` (along with similar matplotlib functions).\n",
    "\n",
    "It's common to see colormaps like ``jet`` (or other rainbow palettes) used in this case, becuase the range of hues gives the impression of providing additional information about the data. However, colormaps with large hue shifts tend to introduce discontinuities that don't exist in the data, and our visual system isn't able to naturally map the rainbow to quantitative distinctions like \"high\" or \"low\". The result is that these visualizations end up being more like a puzzle, and they obscure patterns in the data rather than revealing them. The jet palette is [particularly bad](http://medvis.org/2012/08/21/rainbow-colormaps-what-are-they-good-for-absolutely-nothing/) because the brightest colors, yellow and cyan, are used for intermediate data values. This has the effect of emphasizing uninteresting (and arbitrary) values while deemphasizing the extremes.\n",
    "\n",
    "For sequential data, it's better to use palettes that have at most a relatively subtle shift in hue accompanied by a large shift in brightness and saturation. This approach will naturally draw the eye to the relatively important parts of the data.\n",
    "\n",
    "The [Color Brewer](http://colorbrewer2.org) library has a great set of these palettes. They're named after the dominant color (or colors) in the palette."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"Blues\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Like in matplotlib, if you want the lightness ramp to be reversed, you can add a ``_r`` suffix to the palette name."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"BuGn_r\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Seaborn also adds a trick that allows you to create \"dark\" palettes, which do not have as wide a dynamic range. This can be useful if you want to map lines or points sequentially, as brighter-colored lines might otherwise be hard to distinguish."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"GnBu_d\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remember that you may want to use the `choose_colorbrewer_palette` function to play with the various options, and you can set the ``as_cmap`` argument to ``True`` if you want the return value to be a colormap object that you can pass to seaborn or matplotlib functions."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Sequential palettes with `cubehelix_palette`\n",
    "\n",
    "The [cubehelix](http://www.mrao.cam.ac.uk/~dag/CUBEHELIX/) color palette system makes sequential palettes with a linear increase or decrease in brightness and some variation in hue. This means that the information in your colormap will be preserved when converted to black and white (for printing) or when viewed by a colorblind individual.\n",
    "\n",
    "Matplotlib has the default cubehelix version built into it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"cubehelix\", 8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Seaborn adds an interface to the cubehelix *system* so that you can make a variety of palettes that all have a well-behaved linear brightness ramp.\n",
    "\n",
    "The default palette returned by the seaborn `cubehelix_palette` function is a bit different from the matplotlib default in that it does not rotate as far around the hue wheel or cover as wide a range of intensities. It also reverses the order so that more important values are darker:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.cubehelix_palette(8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Other arguments to `cubehelix_palette` control how the palette looks. The two main things you'll change are the ``start`` (a value between 0 and 3) and ``rot``, or number of rotations (an arbitrary value, but probably within -1 and 1),"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.cubehelix_palette(8, start=.5, rot=-.75))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also control how dark and light the endpoints are and even reverse the ramp:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAdgAAABQCAYAAAC6TWSYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvqOYd8AAAAmVJREFUeJzt2C+rk2Ecx+F7YzBBPCqiom5vwSRoOFgMBqPxZG0Gm8VksRlsmk80GgwWk4LJV7Cxqagcjn8QHMh5fA0b+/Ib87r6D77t8zx3r+u6rgEAa9WvHgAA20hgASBAYAEgQGABIEBgASBAYAEgQGABIEBgASBAYAEgQGABIEBgASBAYAEgYLDq4e7ubpvP5+vcsjEmk0m7fPNK9YyYD6/etxv3blXPiHn99GXbe3K3ekbE/v1n7cGLR9UzYh7fftiev9uvnhFz5+peezN7Wz0j5vr4Wjtc/KieEdFvvXZyuLPUzcqBnc/nbTqdrnq+8WafZtUToj5++1w9IerL96/VE2IOfh9WT4j6ufhVPSHqz99F9YSoo+6oekJGb/kHX0/EABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAEDBY9XA0Gq1zx8YZXxxXT4i6dPZC9YSo86fOVU+IOXP8dPWEqJ3hieoJUccGw+oJUf3edv639Vtv6Zte13VdYAsA/Ne281MDAIoJLAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABAgsAAQILAAECCwABPwDG/A+RmPObYIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.cubehelix_palette(8, start=2, rot=0, dark=0, light=.95, reverse=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default you just get a list of colors, like any other seaborn palette, but you can also return the palette as a colormap object that can be passed to seaborn or matplotlib functions using ``as_cmap=True``."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([-0.33617823,  2.43880787,  1.67480892,  1.98975273,  0.99071373]),\n",
       " array([ 0.34208098, -2.52029976,  1.44056054, -0.2604635 ,  0.94806489]))"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x, y = np.random.multivariate_normal((0, 0), ((1, -.5), (-.5, 1)), size=300).T\n",
    "x[:5], y[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/luke.thompson/miniconda3/envs/python3/lib/python3.7/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a2c14d048>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap = sns.cubehelix_palette(light=1, as_cmap=True)\n",
    "sns.kdeplot(x, y, cmap=cmap, shade=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To help select good palettes or colormaps using this system, you can use the `choose_cubehelix_palette` function in a notebook to launch an interactive app that will let you play with the different parameters. Pass ``as_cmap=True`` if you want the function to return a colormap (rather than a list) for use in function like `hexbin`.\n",
    "\n",
    "**Custom sequential palettes with `light_palette` and `dark_palette`**\n",
    "\n",
    "For a simpler interface to custom sequential palettes, you can use `light_palette` or `dark_palette`, which are both seeded with a single color and produce a palette that ramps either from light or dark desaturated values to that color. These functions are also accompanied by the `choose_light_palette` and `choose_dark_palette` functions that launch interactive widgets to create these palettes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.light_palette(\"green\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWkAAABQCAYAAADbeYSfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvqOYd8AAAAhpJREFUeJzt2DFKXGEUhuFjsB4HERxhElOlSpUqq7CcVnADbmGW4GzFJQwpsgCrdCYZvIIIlhHhZgUpcpmf/yuepz/wVW9xDsZxHAuASO96DwDg30QaIJhIAwQTaYBgIg0QTKQBgok0QDCRBggm0gDBRBogmEgDBBNpgGCHUw9Xq1UNw7DPLTG2221dfL3oPaOZ2++3dfnlsveMJuav89rcber683XvKU1s7ja1/rTuPaOZ9Y913Xy86T2jidlyVlffrv77bnKkh2Go3W439Tzew++H3hOaevz12HtCE29/3qqq6unnU+cl7TzfP/ee0NTL/UvvCVG8OwCCiTRAMJEGCCbSAMFEGiCYSAMEE2mAYCINEEykAYKJNEAwkQYIJtIAwUQaIJhIAwQTaYBgIg0QTKQBgok0QDCRBggm0gDBRBogmEgDBBNpgGAiDRBMpAGCiTRAMJEGCCbSAMFEGiCYSAMEE2mAYCINEEykAYKJNEAwkQYIJtIAwUQaIJhIAwQTaYBgIg0QTKQBgok0QDCRBggm0gDBRBogmEgDBBNpgGAiDRBMpAGCiTRAMJEGCHY49XCxWOxzR5yz5VnvCU2dvj/tPaGJ+eu8qqpOPpx0XtLO8flx7wlNHZ0f9Z7QxGw5m3R3MI7juOctAOyJdwdAMJEGCCbSAMFEGiCYSAMEE2mAYCINEEykAYKJNEAwkQYIJtIAwUQaINhfqRY3j5p64L8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.dark_palette(\"purple\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These palettes can also be reversed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWkAAABQCAYAAADbeYSfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvqOYd8AAAAgRJREFUeJzt2DFKA0EAheExESEgqRRBPEAabyDY5gyeIGWOk8rSM1jYeAYvYCAIgo1BCAiy1hYWWTLMY/m+ZquBN83PMkdd13UFgEij1gMA+J9IAwQTaYBgIg0QTKQBgok0QDCRBggm0gDBRBogmEgDBBNpgGAiDRDsuO/Bm5v7stlsD7klxuvrssznD61nVPP4eFeWy6fWM6qYzS7KYnFdVquX1lOqWCyuy/Pze+sZ1dzeXpT3gV5vNCrl/Hz/c70jvdlsy3r92fd4vLe3r9YTqvr42LWeUMV2+/3nO0S73U/rCVX9DPt6e/PcARBMpAGCiTRAMJEGCCbSAMFEGiCYSAMEE2mAYCINEEykAYKJNEAwkQYIJtIAwUQaIJhIAwQTaYBgIg0QTKQBgok0QDCRBggm0gDBRBogmEgDBBNpgGAiDRBMpAGCiTRAMJEGCCbSAMFEGiCYSAMEE2mAYCINEEykAYKJNEAwkQYIJtIAwUQaIJhIAwQTaYBgIg0QTKQBgok0QDCRBggm0gDBRBogmEgDBBNpgGAiDRBMpAGCiTRAsOO+B6+upofcEefy8rT1hKrOziatJ1QxnZ78+Q7RZDJuPaGq8UCvN+r5S3zUdV132CkAHIrnDoBgIg0QTKQBgok0QDCRBggm0gDBRBogmEgDBBNpgGAiDRBMpAGCiTRAsF+aHjNUCObZpwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.light_palette(\"navy\", reverse=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "They can also be used to create colormap objects rather than lists of colors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pal = sns.dark_palette(\"palegreen\", as_cmap=True)\n",
    "sns.kdeplot(x, y, cmap=pal);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default, the input can be any valid matplotlib color. Alternate interpretations are controlled by the ``input`` argument. Currently you can provide tuples in ``hls`` or ``husl`` space along with the default ``rgb``, and you can also seed the palette with any valid ``xkcd`` color."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.light_palette((210, 90, 60), input=\"husl\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.dark_palette(\"vomit green\", input=\"xkcd\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the default input space for the interactive palette widgets is `husl`, which is different from the default for the function itself, but much more useful in this context."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Diverging color palettes\n",
    "\n",
    "The third class of color palettes is called \"diverging\". These are used for data where both large low and high values are interesting. There is also usually a well-defined midpoint in the data. For instance, if you are plotting changes in temperature from some baseline timepoint, it is best to use a diverging colormap to show areas with relative decreases and areas with relative increases.\n",
    "\n",
    "The rules for choosing good diverging palettes are similar to good sequential palettes, except now you want to have two relatively subtle hue shifts from distinct starting hues that meet in an under-emphasized color at the midpoint. It's also important that the starting values are of similar brightness and saturation.\n",
    "\n",
    "It's also important to emphasize here that using red and green should be avoided, as a substantial population of potential viewers will be [unable to distinguish them](http://en.wikipedia.org/wiki/Color_blindness).\n",
    "\n",
    "It should not surprise you that the Color Brewer library comes with a set of well-choosen diverging colormaps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"BrBG\", 7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"RdBu_r\", 7))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another good choice that is built into matplotlib is the ``coolwarm`` palette. Note that this colormap has less contrast between the middle values and the extremes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.color_palette(\"coolwarm\", 7))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Custom diverging palettes with `diverging_palette`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also use the seaborn function `diverging_palette` to create a custom colormap for diverging data. (Naturally there is also a companion interactive widget, `choose_diverging_palette`). This function makes diverging palettes using the ``husl`` color system. You pass it two hues (in degreees) and, optionally, the lightness and saturation values for the extremes. Using ``husl`` means that the extreme values, and the resulting ramps to the midpoint, will be well-balanced"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.diverging_palette(220, 20, n=7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.diverging_palette(145, 280, s=85, l=25, n=7))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ``sep`` argument controls the width of the separation between the two ramps in the middle region of the palette."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 504x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.diverging_palette(10, 220, sep=80, n=7))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's also possible to make a palette with the midpoint is dark rather than light."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAaAAAABQCAYAAABf06H0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvqOYd8AAAAi9JREFUeJzt2L9K1mEch+Gf5WQNJaKZx+Lu0BDU1GAQNEdbQ9ASEQ11AE01NERFQ0O7x2Km9I/QUd7OIFB8usWua//CZ3m44ZmbzWazCQD+sXP1AAD+TwIEQEKAAEgIEAAJAQIgIUAAJAQIgIQAAZAQIAASAgRAQoAASAgQAIn54x4+e7s3/do/PMktp8aTO6vT3Yfv6hnDvHx8c7p+6349Y5iPb15M6+vr9Ywhtra2po3b1+oZw3x+9Wm68XSznjHM+wevp80P9+oZQywtLE7PNx4d6ebYAfq1fzh9/302AzRN07T346CeMNTO7rd6wlDb29v1hGG+7O3UE4b6+nO3njDU7sHZfntH4QsOgIQAAZAQIAASAgRAQoAASAgQAAkBAiAhQAAkBAiAhAABkBAgABICBEBCgABICBAACQECICFAACQECICEAAGQECAAEgIEQEKAAEgIEAAJAQIgIUAAJAQIgIQAAZAQIAASAgRAQoAASAgQAAkBAiAhQAAkBAiAhAABkBAgABICBEBCgABICBAACQECICFAACQECICEAAGQECAAEgIEQEKAAEgIEAAJAQIgIUAAJAQIgIQAAZAQIAAS88c9vHTx/EnuOHWWFy/UE4ZaXVmqJwy1trZWTxjm6vJqPWGoK5dX6glDrVw4m29vaWHxyDdzs9lsNmALAPyVLzgAEgIEQEKAAEgIEAAJAQIgIUAAJAQIgIQAAZAQIAASAgRAQoAASAgQAIk/Muk4qfYOQpEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 504x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.palplot(sns.diverging_palette(255, 133, l=60, n=7, center=\"dark\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Changing default palettes with `set_palette`\n",
    "\n",
    "The `color_palette` function has a companion called `set_palette`. The relationship between them is similar to the pairs covered in the aesthetics tutorial. `set_palette` accepts the same arguments as `color_palette`, but it changes the default matplotlib parameters so that the palette is used for all plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sinplot(flip=1):\n",
    "    x = np.linspace(0, 14, 100)\n",
    "    for i in range(1, 7):\n",
    "        plt.plot(x, np.sin(x + i * .5) * (7 - i) * flip)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_palette(\"Reds\")\n",
    "sinplot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `color_palette` function can also be used in a ``with`` statement to temporarily change the color palette."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with sns.color_palette(\"PuBuGn_d\"):\n",
    "    sinplot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The default palette set by `sns.set_palette()` before the `with` statement is unchanged:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sinplot()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
